Screening for post-TB lung disease at TB treatment completion: Are symptoms sufficient?

Pulmonary TB survivors face a high burden of post-TB lung disease (PTLD) after TB treatment completion. In this secondary data analysis we investigate the performance of parameters measured at TB treatment completion in predicting morbidity over the subsequent year, to inform programmatic approaches to PTLD screening in low-resource settings. Cohort data from urban Blantyre, Malawi were used to construct regression models for five morbidity outcomes (chronic respiratory symptoms or functional limitation, ongoing health seeking, spirometry decline, self-reported financial impact of TB disease, and death) in the year after PTB treatment, using three modelling approaches: logistic regression; penalised regression with pre-selected predictors; elastic net penalised regression using the full parent dataset. Predictors included demographic, clinical, symptom, spirometry and chest x-ray variables. The predictive performance of models were examined using the area under the receiver-operator curve (ROC AUC) values. Key predictors were identified, and their positive and negative predictive values (NPV) determined. The presence of respiratory symptoms at TB treatment completion was the strongest predictor of morbidity outcomes. TB survivors reporting breathlessness had higher odds of spirometry decline (aOR 20.5, 95%CI:3–199.1), health seeking (aOR 10.2, 2.4–50), and symptoms or functional limitation at 1-year (aOR 16.7, 3.3–133.4). Those reporting activity limitation were more likely to report symptoms or functional limitation at 1-year (aOR 4.2, 1.8–10.3), or severe financial impact of TB disease (aOR2.3, 1.0–5.0). Models were not significantly improved by including spirometry or imaging parameters. ROC AUCs were between 0.65–0.77 for the morbidity outcomes. Activity limitation at treatment completion had a NPV value of 78–98% for adverse outcomes. Our data suggest that whilst challenging to predict the development of post-TB morbidity, the use of symptom screening tools at TB treatment completion to prioritise post-TB care should be explored. We identified little benefit from the additional use of spirometry or CXR imaging.


Introduction
There are over 10 million incident cases of tuberculosis (TB) each year [1].Over 85% of TB patients successfully complete treatment, with an estimated 155 million TB survivors alive in 2020 [2], but many TB survivors continue to experience physical, psychological and socioeconomic morbidity long after treatment completion [3][4][5][6][7].Post-TB lung disease (PTLD) is a well described sequela of TB disease, with approximately half of those successfully treated for pulmonary TB (PTB) in low-and middle-income countries (LMICs) left with respiratory symptoms, impaired spirometry, or structural lung damage [8][9][10].Although there is some recovery over time, a minority of PTB survivors continue to experience morbidity even several years after TB treatment completion [11], and PTLD has been associated with functional impairment, loss of income, and ongoing health seeking [6,12,13].
In response to this emerging data on the burden of PTLD, several National TB Programmes (NTPs) have considered screening for PTLD at TB treatment completion [14], and the provision of ongoing clinical care to those with residual lung damage.However, there is a lack of data to inform screening approaches.It remains unclear whether symptoms, spirometry, or imaging could be used to identify patients with residual PTLD who are at risk of adverse outcomes.The costs and feasibility of these approaches have not been described.Similarly the potential impact of PTLD screening on patients is not well understood-benefits may include linkage to post-TB care and health education, but harms may include stigma related to a chronic disease diagnosis, and the time and cost associated with further investigation.There is a need for more robust evidence around screening to inform decision making by NTPs around implementation [15].
In this paper we perform a secondary analysis of published cohort data from Malawi [9], to investigate the performance of symptom questions, spirometry, and chest radiographs (CXR) at TB treatment completion in predicting adverse outcomes in the year after TB treatment completion, in order to inform programmatic approaches to PTLD screening in low-resource settings.

Methods
This exploratory analysis used data from a prospective cohort study of 405 PTB-survivors in urban Blantyre, Malawi, which has been described in detail elsewhere [9].Briefly, adults �15-years successfully completing treatment for a first episode of drug-sensitive PTB were sequentially recruited between February 2016 -April 2017.Respiratory symptoms, quality of life (St George's Respiratory Questionnaire (SGRQ) and the EQ-5D-3L tool) and socioeconomic parameters were measured at TB treatment completion, and at 6-and 12-months thereafter.Participants completed questionnaires in the local language (Chichewa).Postbronchodilator American Thoracic Society (ATS)-standard spirometry was performed at each study visit, and digital CXRs were completed at TB treatment completion.All-cause deaths were confirmed with family and friends, where participants failed to attend study follow-up visits.It was not possible to determine the cause of death.All CXRs were reported independently by both a pulmonologist (JM) and consultant radiologist (EJ) using a specifically designed reporting tool (S1 Text) with consensus review to generate final results.

Data analysis
Adverse outcomes thought to be relevant to patient lives were defined by the study team (Table 1).The frequency and overlap between these outcomes were described.Change in spirometry over time was included as an outcome of interest, rather than absolute spirometry at 1-year, on the basis that the trajectory of decline may be particularly important to long-term outcomes.TB retreatment was strongly associated with death, and so was not examined separately.
Two approaches were used to select predictors and construct models for each outcome.Firstly, a parsimonious set of potential predictors were selected a priori by the study team (S2 Text) and models were constructed in a layered fashion with sequential inclusion of chosen demographic, clinical, spirometry, and finally CXR variables.Both logistic regression models and penalised regression models were applied to these pre-selected variable sets.Firth's correction was used to obtain estimates for models using death as the outcome.Secondly, variable selection via elastic net penalised regression models was used to identify key predictors from amongst the larger set of parameters available within the parent data set (S3 Text).This approach was taken to evaluate if our a priori predictor sets were incomplete and missing highly predictive or relevant variables.For all penalised regression models, variable importance factors (VIF) were calculated and plotted.Selected variables under the best performing model were re-fit and estimated coefficients (95% CI) presented.All models were fit under 10-fold cross validation and model performance was visualised using area under the receiveroperator (ROC) curve (AUC).Only demographic, clinical, spirometry and CXR parameters which could reasonably be measured at TB treatment completion in LMICs were included.Missing data were imputed for socioeconomic status at TB treatment completion (n = 33), but complete case analyses were used elsewhere.

Study population
As

Relationship between patient outcomes
The majority of participants experiencing any negative outcome had only a single adverse outcome (Spirometry decline alone 60.6% [43/71]; Severe financial impact alone 51.6% [32/62]; Chronic respiratory symptoms alone 34.2%[25/73]; Unscheduled health seeking alone 37.1% [23/62]).The greatest overlap in adverse outcomes was seen between those with chronic symptoms at 1-year and those reporting unscheduled health seeking over this year: 22.2%(30/135) of those with either of these outcomes experienced both (Fig 1).

Characteristics by individual adverse outcomes, in univariate analysis
As previously described, the majority of those who died were HIV-positive (90.1%, 10/11), with CD4 counts below 200 cells/mm 3 at TB treatment completion (80%, 8/10). 9The prevalence of limited walking pace, or �10% parenchymal consolidation on CXR at TB treatment completion was higher amongst those who subsequently died, compared to those who survived (54.5% vs. 26.0%,p = 0.035 and 27.3% vs. 7.1%, p = 0.013 respectively) (Table 2).A higher proportion of those experiencing accelerated spirometry decline were female, compared to those with more stable or improving spirometry (40.8% vs. 26.1%,p = 0.017).Baseline spirometry was more likely to be normal at treatment completion, and baseline BMIs higher amongst those with accelerated decline (p = 0.008 and p<0.001 respectively), perhaps reflecting some regression to the mean.
The presence of symptoms including regular cough, regular breathlessness, slower walking pace, or limitation of activities at TB treatment completion were associated with unscheduled respiratory health seeking, symptoms or functional limitation, and self-reported severe financial impact of TB disease by 1-year after treatment completion.
Poverty at TB treatment completion, defined by having a maximum of primary school education or being in the lowest two socioeconomic quintiles in urban Blantyre, was associated with reporting a severe financial impact from TB disease (p = 0.024 and p = 0.005, respectively).

Predictors of adverse outcomes, in pre-specified generalised logistic regression models
Multivariable regression models constructed to identify predictors of death were unstable (Table A in S4 Text).Across all other models, demographic and clinical parameters were consistently associated with outcomes.Few statistically significant associations were observed between pre-selected spirometry or imaging parameters in adjusted models, when added alongside demographic and clinical variables (Table 3, Tables B-E in S4 Text).
Patients with regular breathlessness at TB treatment completion had significantly higher odds of an accelerated spirometry decline, ongoing health seeking, and symptoms or functional limitation at 1-year.These associations were large and statistically significant across models (Fig 2).Those reporting activity limitation at treatment completion had consistently increased odds of respiratory symptoms or activity limitation at 1-year, and were more likely to report a severe financial impact of TB disease (Table 3, Tables D & E in S4 Text).Weekly cough at treatment completion was not correlated with respiratory, health seeking or socioeconomic outcomes.
HIV-positive participants had lower odds of accelerated spirometry decline and unscheduled respiratory health seeking in the year after TB treatment completion compared to HIV-  negative participants.This association persisted in models controlling for the extent of PTLD (symptoms, spirometry and imaging) at treatment completion.
Poverty was associated with both adverse socioeconomic outcome and accelerated spirometry decline: in models controlling for the extent of PTLD at TB treatment completion, participants in the poorest two socioeconomic quintiles had 2.4 (95% CI: 1.1-5.2) and 2.8 (95% CI: 1.2-6.6)fold higher odds of these outcomes respectively, compared to those in wealthier quintiles.Males had reduced odds of spirometry decline compared to females across all models, but gender was not associated with any other patient outcome.Spirometry at TB treatment completion was predictive of symptoms or functional limitation at 1-year only.Although no association was observed with the pattern of spirometry deficit at treatment completion, individuals with higher FEV 1 % predicted values at TB treatment completion had lower odds of symptoms or limitation at 1-year, whilst those with higher FVC % predicted values had increased odds of ongoing symptoms or limitation at 1-year.CXR parameters at treatment completion were not associated with any of the patient outcomes.
A sensitivity analysis investigating the relationship between pre-specified parameters and outcomes amongst those with microbiologically confirmed PTB disease only demonstrated similar patterns of association (S5 Text).

Predictors of adverse outcomes, with penalised logistic regression models using pre-specified variables
The variable reduced models showed similar relationships to those seen above (S6 Text).Several variables were dropped in the models for respiratory symptoms or limitation at 1-year, but the presence of symptoms at treatment completion remained the most important predictor of outcome: participants with weekly breathlessness or limitation of activities at treatment completion had 16.6 (3.6-122.7)and 4.2 (1.8-10.0)fold higher odds of reporting either of these symptoms one year later, compared to those without symptoms at treatment completion.
HIV was retained as a predictor of spirometry decline or ongoing health seeking.The strength and significance of associations with clinical outcomes was similar, but HIV-status was also significantly associated with socioeconomic outcomes here: HIV-positive adults with CD4 counts <200cells/mm 3 had 2.5 (1.0-6.2) times higher odds of reporting severe financial effects of TB disease, compared to HIV-negative adults, controlling for the extent of lung pathology (S6 Text).
In the reduced model for spirometry decline, a positive correlation was observed between FVC % predicted at TB treatment completion and accelerated spirometry decline in the following year.However, no other statistically significant associations were observed between spirometry measures or CXR parameters at TB treatment completion, and the various outcomes.

Predictors of adverse outcomes, with penalised regression models derived from the full parent dataset
The variable importance estimates (S7 Text) and models fit from the full parent dataset (S8 Text) confirm that variables describing participant demographic, socioeconomic, and symptom characteristics at TB treatment completion were the most important predictors of patient outcome.The precise variables included to represent these concepts were different to those pre-selected for use in the models above, but the broad themes were consistent.
Clinical measurements including oxygen saturation, heart rate, and 6-minute walk distance at TB treatment completion also emerged as important predictors of patient outcomes using this approach.However, the importance of spirometry and CXR parameters remained limited, with statistically significant associations observed between FVC % predicted and % parenchymal abnormality, and spirometry decline only.

Model performance
Regardless of the predictor set or variable selection process used, the ROC curves generated for all outcomes showed limited AUC, suggesting limited predictive power.There was little difference between the AUCs generated by the full and penalised regression models constructed using the pre-selected variable sets (Fig 3, S9 Text), and those derived from the full parent data set (Fig 4), suggesting that the a priori predictor sets captured the main constructs of value.
Death was the hardest variable to predict with unstable estimation due to small numbers.The AUCs observed for models of health seeking and the financial impact of TB disease were limited (maximum 0.65 and 0.66), whilst those for the models of symptoms and spirometry decline were higher (maximum 0.77 and 0.74).The largest increments were observed when clinical and symptom parameters were added to baseline demographic and socioeconomic characteristics in the models constructed using the a-priori data sets.Little further improvement in AUC was seen when spirometry and CXR parameters were added (Fig 3).

Performance of individual symptom questions in screening for adverse outcomes
Because symptoms at TB treatment completion were highlighted across analyses as key predictors, the sensitivity, specificity, positive and negative predictive values (PPV and NPV) of a range of individual symptom questions for outcomes were examined.Specificity and PPVs were limited, but sensitivity and NPVs were higher (S10 Text).The performance of individual symptom questions was superior to binary spirometry and imaging parameters (S11 Text).
The symptom questions with the highest NPV across outcomes were limitation of activities (reported by 205/403 (50.6%),NPV 78.2-98.2%),and breathlessness when walking up hills (reported by 176/405 (43.5%),NPV 77.4-99.5%),with the highest values seen for mortality and ongoing symptoms or limitation at 1-year (Table 4).Similar patterns were observed in a sensitivity analysis of those treated for microbiologically confirmed disease only (S12 Text).
The prevalence of abnormal patterns of spirometry, residual cavitation, and consolidation on imaging were significantly higher amongst those who reported limitation of activities at treatment completion, compared to those who did not (S13 Text).

Discussion
In this secondary analysis of prospective cohort data from Malawi, we show that it is challenging to accurately predict morbidity after TB treatment completion at the individual level, but that demographic, clinical, and symptom parameters are strongly associated with adverse outcomes.Simple symptom questions at treatment completion have moderate negative predictive value for morbidity outcomes within this data set, with little incremental benefit from the additional use of spirometry and imaging.
We have previously shown that a substantial minority of adults completing treatment for PTB experience adverse respiratory, health seeking, and socioeconomic outcomes in the year after TB treatment completion [6,9].The further analyses conducted here show that it is difficult to predict these outcomes at the individual level: ROC AUC values for all of the predictive models developed were poor, and changed little with the different modelling approaches used, suggesting that this is not a function of the variables included but rather a genuine limitation of outcome prediction within this dataset.However, demographic factors and symptoms were strong predictors of morbidity across these models, with individual symptom questions showing moderate NPVs for adverse outcomes.This was in contrast to imaging and spirometry parameters, which were poorly associated with patient outcomes and did little to improve the predictive capacity of models.
Our findings suggest that it will likely be challenging to develop a screening tool which accurately predicts adverse outcomes amongst PTB survivors at the individual level.One possible response to this finding-if confirmed in other data sets-would be to offer routine post-TB follow up to all PTB survivors, accepting that only a small proportion of these individuals will go on to develop post-TB morbidity.This would be an inclusive approach and may  provide reassurance to many patients.However, significant funding and staff resources would be required to implement this approach.There may also be patient harms associated with routine follow-up including the ongoing direct and indirect costs of additional health care visits [18], stigma related to ongoing contact with TB services [19], and anxiety around a diagnosis of chronic condition, and uptake may be limited amongst those who are asymptomatic at treatment completion.In-depth qualitative work and health economic analyses would be needed to explore the patient and health system implications of routine post-TB follow up, and likely demand for these services.
Where there is a wish to provide more targeted care to a limited number of TB survivors only, our data suggest that a symptom screening approach could be used to direct this.The absence of symptoms such as exertional breathlessness and functional impairment at TB treatment completion could be used as a 'rule out' test, with those who are asymptomatic discharged from care.We acknowledge that there are limitations with this approach.Symptoms are a relatively blunt tool and within our data set still only half of patients would be asymptomatic and discharged at TB treatment completion using this approach.Between 13-22% of those who are discharged may go on to experience accelerated spirometry decline or respiratory health seeking, or report a severe financial impact of TB disease.Meanwhile, amongst those symptomatic patients who receive ongoing follow-up, still only a minority would go on to develop adverse outcomes.
Although this is also an imperfect approach, it is low cost, requires minimal training and time, could be implemented at the programmatic level, and would half the number of patients offered follow-up after treatment completion.Post-TB services built around patient symptoms may be more acceptable and readily adopted by patients who still feel unwell and perceive a need for ongoing review [20], and points of re-entry in to respiratory or post-TB care could be established for those who are discharged but deteriorate over time [21].A symptom based approach may also allow those with other causes of chronic symptoms to be identified, including non-TB chronic respiratory diseases (E.g.COPD, occupational lung diseases), cardiovascular disease, deconditioning and muscle loss related to severe illness, anaemia, or advanced HIV, with linkage of symptomatic patients to ongoing care [22,23].There may therefore be several positive outcomes from such an approach.
Of note-our data suggest that the ability to predict adverse outcomes does not improve with the addition of spirometry and CXR data to simple symptom screening.Where NTPs are interested in focused post-TB care, it may therefore be reasonable to use simple symptom questionnaires to direct this, without further investigation.This finding is particularly relevant to low-resource settings, where care is decentralised and delivered in health centres by nursing staff and TB officers with limited access to respiratory diagnostics.The choice of symptom questions and their wording will require optimisation, and may vary between settings.
Lastly, in this analyses we have investigated the use of screening approaches to identify those at risk of five types of post-TB morbidity.However, as we develop clinical interventions for post-TB patient care, screening approaches may need to be modified in order to identify patients who are eligible for these interventions, and the use of imaging and spirometry alongside symptoms may need to be reconsidered.For example, studies of pulmonary rehabilitation for PTB survivors in LMICs currently use breathlessness to determine eligibility, in an approach similar to that described here, with good preliminary results [24,25].However, interventions such as inhaled bronchodilators are most effective in those with airway obstruction, and spirometry may be needed at the point of TB treatment completion to identify individuals those with obstructive airways disease who are eligible for inhaled therapies.
This study has several important limitations.It was an exploratory secondary analysis, and might therefore be subject to bias.We constructed models for outcomes chosen by the study team, which have not been recognised or validated outside of this study, and we did not consider eligibility for clinical interventions.We were unable to develop strong predictive models for death in the year after TB treatment completion-this was likely due to low event numbers, but may also reflect true challenges in predicting this outcome, and larger data sets will be needed to explore this.The data used were collected from a single study, with a single approach to measuring symptoms, imaging and spirometry, in a single site.The PPV and NPV reported for predicted may differ in other sites where the incidence of adverse outcomes in the post-TB period differs.Critically, the patient outcomes evaluated were measured at 1-year after treatment completion only.We also explored parallel use of tests only, and did not explore a two-or three-stage screening process with sequential use of tests.Although we hypothesise that a symptom-based approach would be cost-effective and acceptable, this was not formally evaluated.These issues must be explored in other datasets and settings.
However, despite these limitations, our analysis is relevant to the development of post-TB care services in LMICs, and provides evidence to inform NTP decision making about if and how to screen patients at TB treatment completion, in order to determine access to post-TB care.We show that it is challenging to accurately identify those at greatest risk of adverse post-TB outcomes at TB treatment completion.However, if there is a need to prioritise ongoing care, the use of low cost symptom based screening tools may be the most promising approach with little incremental benefit from the additional use of imaging or spirometry.Symptom questions must be refined and optimised, and this symptom-based approach may need to evolve as targeted post-TB interventions become more widely available.However, this is a pragmatic approach which could be used by NTPs at TB treatment completion, as they seek to monitor and improve the long-term wellbeing of TB survivors.

S5
Text.Adjusted odds ratios estimating associations between pre-specified parameters and outcomes, by logistic regression model, including all pre-specified covariates with no variable reduction in microbiology confirmed TB participants only.(DOCX) S6 Text.Multivariable associations (OR (95% CI) between pre-specified parameters and outcomes, in penalised regression models.(DOCX) S7 Text.Variable importance values for prediction of outcome, using full parent data set (Higher value indicates greater importance in predicting outcome).(DOCX) S8 Text.Models constructed for each outcome, from full parent data set.(DOCX) S9 Text.ROC curves for logistic regression models for each outcome, using pre-specified predictor variable sets after variable reduction with penalised regression (Group 1: Demographic only; Group 2: Demographic plus clinical; Group 3: Demographic, clinical, spirometry; Group 4: Demographic, clinical, spirometry and CXR).(DOCX) S10 Text.Sensitivity, specificity, and predictive values of individual symptoms questions for each outcome.(DOCX) S11 Text.Performance of indicators on CXR at TB treatment completion, in screening for adverse patient outcomes.(DOCX) S12 Text.Performance of question about limitation of activity and shortness of breath on hills at TB treatment completion, in screening for adverse patient outcomes among TB microbiology confirmed participants only.(DOCX) S13 Text.Patient characteristics, stratified by presence or absence of limitation of activities at TB treatment completion.(DOCX)

Table 2 . Participant characteristics, for whole cohort and those experiencing individual outcomes, with univariate relationships between parameters and outcomes shown by density of shading (P<0.001, p<0.01, p<0.05).
Clinical questions derived from self-reported answers to St George's Questionnaire: Regular cough: cough on �several days/week, for past 3-months; Regular breathlessness: shortness of breath on �several days/week, for past 3-months; Limited walking: needs to walk slower than others, or to stop for a rest; Limitation of activities: chest symptoms preventing 1-2 normal activities, most activities, or all activities.¶ Post-bronchodilator spirometry data meeting ATS standards included only (n = 305), and standardised by GLI Black reference ranges.

Table 3 . Adjusted odds ratios estimating associations between pre-specified parameters and outcomes, by logistic regression model, including all pre-specified covariates with no variable reduction.
*Variables where '-' given are unstable and OR not interpretable.https://doi.org/10.1371/journal.pgph.0002659.t003